
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "23"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 155 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 150 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	74.260076	97.461710	116.274078	171.641849	20.811251	32.277733	48.795644	91.801024	0.0185	0.0162	0.0016	1.150850	1.114279
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	235.628394	59.671540	158.755321	156.226171	33.944580	68.973116	92.913379	137.297372	0.0194	0.0177	0.0008	1.111053	1.090280
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	30.060151	7.331431	64.003315	51.389960	35.244209	55.949593	64.887056	71.916074	0.0190	0.0178	0.0014	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	287.011438	69.678234	190.652856	186.235760	34.244778	68.109075	140.360361	208.664265	0.0187	0.0169	0.0013	1.126142	1.081504
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	284.672923	97.832713	177.332843	161.499148	37.513162	45.106201	189.773451	165.428948	0.0176	0.0180	0.0005	1.143963	1.117548
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	333.993221	338.840088	inf	inf	19.825287	51.551706	86.889889	365.162246	nan	nan	nan	0.000000	0.000000
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	193.974932	61.441433	214.922552	197.944023	22.513186	41.104010	54.232202	69.012587	0.0172	0.0173	0.0006	1.095720	1.074774
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	345.490094	67.326415	391.545757	250.004453	26.813401	55.885975	190.723985	356.046526	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	254.283856	70.508030	59.491948	54.476987	11.874645	16.656258	208.395942	256.880010	0.0178	0.0178	0.0008	1.147797	1.136537
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	102.895216	52.849851	38.588521	35.975398	19.901356	8.771227	377.493288	432.180871	0.0185	0.0170	0.0008	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	92.904856	103.414445	269.101933	222.811344	33.737768	21.238715	166.521090	90.079599	0.0178	0.0169	0.0010	1.092438	0.906762
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	49.495729	65.403651	80.610254	67.728848	36.160276	25.756135	281.642658	182.701656	0.0180	0.0173	0.0005	1.141201	1.145678
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	42.113148	49.500837	67.055659	59.553589	34.563500	42.837254	241.849606	167.270662	0.0182	0.0171	0.0014	1.113760	1.118076
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	66.273844	56.028512	82.526332	67.947108	52.217607	31.399380	354.668105	181.683452	0.0181	0.0174	0.0013	1.112610	1.119490
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	40.747222	51.891508	74.274215	71.219768	39.345072	34.539968	221.884088	208.677997	0.0181	0.0169	0.0007	1.120847	1.120042
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	36.538853	52.149587	79.074985	78.323548	43.410676	41.799119	304.760105	313.166268	0.0185	0.0171	0.0007	1.144674	1.142212
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.109395	7.316857	37.849264	29.609052	279.357774	108.448690	1191.390758	624.656968	0.0175	0.0169	0.0005	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	48.503424	63.089403	70.111928	62.120301	49.760127	31.757948	245.186330	161.852567	0.0188	0.0171	0.0005	1.116028	1.120388
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	62.479810	61.307982	63.804631	49.177221	52.364055	36.015792	441.140536	188.528560	0.0177	0.0171	0.0008	0.774838	0.777921
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	34.701366	46.052028	58.470972	49.654576	25.652360	19.989379	44.992610	24.558671	0.0180	0.0174	0.0006	0.000000	0.000000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	44.811799	44.146912	56.399968	53.416889	52.106934	36.827693	247.630546	118.707399	0.0176	0.0169	0.0006	1.151743	1.150539
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	46.463924	50.774608	96.917997	77.757321	47.040410	35.120807	485.369273	197.877707	0.0180	0.0173	0.0007	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	37.683979	52.675908	51.281533	50.800436	30.305086	35.154591	528.567960	506.145029	0.0181	0.0171	0.0007	1.069724	1.067723
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	6.751462	6.483619	46.303860	36.426738	265.542828	125.070342	1654.154190	896.045497	0.0170	0.0167	0.0005	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	45.418007	55.339206	71.327988	62.155303	17.999309	15.980086	34.095675	22.931658	0.0180	0.0175	0.0013	1.086751	1.090947
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	42.319669	50.461137	71.850973	64.902324	42.419174	44.825848	197.887472	143.092462	0.0185	0.0169	0.0012	1.035442	1.036338
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-1.318369	-1.318369	-1.270881	-1.270881	-0.651706	-0.651706	-0.774639	-0.774639	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	102.156831	64.829247	108.226413	71.153800	22.906208	8.589977	456.131347	184.120508	0.0171	0.0169	0.0007	1.100866	1.109153
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	52.494452	74.706906	157.389950	144.688746	58.875142	41.083457	456.905293	353.568041	0.0174	0.0166	0.0006	0.000000	0.000000
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	36.926684	38.079378	37.542221	33.311669	16.652357	6.518594	208.554149	148.654548	0.0169	0.0175	0.0010	1.117342	1.123398
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	34.062206	37.870452	36.338108	30.918755	11.594234	8.993143	377.059748	217.156141	0.0173	0.0172	0.0007	1.044727	1.051919
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	30.103851	44.882746	35.419942	34.337336	7.373243	7.238068	244.409071	206.044488	0.0182	0.0167	0.0012	0.788487	0.781238
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	40.739921	43.384506	39.015866	36.487898	10.978964	11.641607	242.098222	222.270723	0.0182	0.0167	0.0016	1.097424	1.099562
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	52.953365	57.714615	78.832170	66.816467	38.636362	30.646337	501.940854	254.956389	0.0179	0.0169	0.0005	1.116766	1.122599
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0181	0.0171	0.0009	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	84.224029	61.515956	107.608890	71.058645	72.614721	29.142795	1652.835547	444.188567	0.0173	0.0172	0.0008	1.089558	1.102302
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0174	0.0167	0.0006	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0168	0.0170	0.0006	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	56.335860	90.782596	113.739755	108.633467	72.539933	59.567465	418.552707	374.485007	0.0173	0.0166	0.0006	0.000000	0.000000
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	49.914680	36.042917	54.007185	38.928163	22.439773	12.104015	563.611441	210.517617	0.0178	0.0167	0.0012	1.084889	1.093730
2459550	RF_maintenance	-	96.71%	96.71%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0389	0.0390	0.0003	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.211012	58.116338	88.340246	71.173680	39.158835	29.150373	457.029548	244.648549	0.0176	0.0174	0.0007	1.087681	1.093556
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	63.144969	61.366679	195.403577	145.558991	9.200896	3.375923	662.449724	249.168869	0.0167	0.0170	0.0006	1.083912	1.091694
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.823376	10.964194	46.519149	43.328104	703.197054	614.593357	22.006220	39.491910	0.0177	0.0171	0.0006	1.109824	1.108940
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	53.815957	49.561140	43.888486	33.673346	36.134565	15.312501	250.400514	126.417122	0.0171	0.0170	0.0006	1.122375	1.135133
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	109.315660	95.185555	168.510910	135.691996	102.621853	48.777181	1328.042059	718.459724	0.0169	0.0166	0.0004	1.141769	1.148987
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	35.386098	38.855180	35.341896	31.589869	23.911875	22.738842	208.357707	194.089278	0.0174	0.0168	0.0006	1.094214	1.100965
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	26.043866	42.010822	29.695465	29.474381	18.051760	14.967883	132.993468	135.981898	0.0182	0.0171	0.0006	1.129167	1.128291
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	73.258266	63.811158	93.885318	68.455619	58.393362	36.140897	750.306346	304.508728	0.0169	0.0176	0.0010	1.102069	1.115363
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	62.656186	85.763586	105.858484	91.541503	54.562962	31.426213	403.104455	226.465999	0.0177	0.0169	0.0005	1.104463	1.110134
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	33.886700	40.855373	31.783299	29.271935	14.855970	12.079666	214.601198	170.697108	0.0180	0.0170	0.0006	1.102219	1.106725
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	75.613049	59.454418	147.519316	98.907923	149.601989	90.252284	494.876334	181.887372	0.0168	0.0168	0.0007	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	58.336979	82.392919	106.322982	105.159296	60.887984	65.168616	366.189011	341.287235	nan	nan	nan	1.390362	1.362447
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	71.225347	60.833817	128.453755	98.426808	166.783244	86.017876	804.411499	343.636625	0.0182	0.0171	0.0008	1.099743	1.105535
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.343000	8.220912	34.551212	26.944087	236.253906	155.246703	1046.447166	553.106167	0.0187	0.0177	0.0009	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	79.002135	59.903068	133.352543	110.304486	127.913437	41.106447	143.214322	83.692269	0.0171	0.0170	0.0007	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	52.642456	62.611880	94.172954	88.673766	69.144553	47.049525	314.550779	278.426725	0.0107	0.0097	0.0018	1.129295	1.136206
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	76.473019	64.415997	192.705347	154.817956	83.871317	41.485947	796.483694	371.903248	0.0067	0.0072	0.0073	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 23 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 23, Node 0:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 23: 2459691

Antenna 23: 2459690

Antenna 23: 2459689

Antenna 23: 2459688

Antenna 23: 2459687

Antenna 23: 2459686

Antenna 23: 2459685

Antenna 23: 2459684

Antenna 23: 2459676

Antenna 23: 2459675

Antenna 23: 2459674

Antenna 23: 2459673

Antenna 23: 2459672

Antenna 23: 2459671

Antenna 23: 2459670

Antenna 23: 2459669

Antenna 23: 2459668

Antenna 23: 2459665

Antenna 23: 2459664

Antenna 23: 2459663

Antenna 23: 2459662

Antenna 23: 2459661

Antenna 23: 2459660

Antenna 23: 2459659

Antenna 23: 2459658

Antenna 23: 2459657

Antenna 23: 2459656

Antenna 23: 2459655

Antenna 23: 2459653

Antenna 23: 2459652

Antenna 23: 2459651

Antenna 23: 2459650

Antenna 23: 2459649

Antenna 23: 2459648

Antenna 23: 2459647

Antenna 23: 2459646

Antenna 23: 2459645

Antenna 23: 2459642

Antenna 23: 2459640

Antenna 23: 2459639

Antenna 23: 2459638

Antenna 23: 2459637

Antenna 23: 2459636

Antenna 23: 2459635

Antenna 23: 2459634

Antenna 23: 2459633

Antenna 23: 2459632

Antenna 23: 2459631

Antenna 23: 2459630

Antenna 23: 2459629

Antenna 23: 2459628

Antenna 23: 2459627

Antenna 23: 2459626

Antenna 23: 2459625

Antenna 23: 2459624

Antenna 23: 2459623

Antenna 23: 2459622

Antenna 23: 2459621

Antenna 23: 2459620

Antenna 23: 2459619

Antenna 23: 2459618

Antenna 23: 2459617

Antenna 23: 2459616

Antenna 23: 2459615

Antenna 23: 2459614

Antenna 23: 2459613

Antenna 23: 2459612

Antenna 23: 2459611

Antenna 23: 2459610

Antenna 23: 2459609

Antenna 23: 2459608

Antenna 23: 2459607

Antenna 23: 2459605

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶